Statistical Planning of Translational Research

Department of Medical Statistics

Any trial should start with its careful planning and especially with sample size calculations, since errors in the statistical planning can have severe consequences on both the results and conclusions drawn from the data. In translational research (preclinical and early clinical), false conclusions highly affect subsequent trials and thus, mistakes proliferate, a rather unethical outcome. Furthermore, group sequential designs and adaptive designs including sample size re-estimation provide a flexible research framework and are therefore desirable in all phases of translational research. Especially in preclinical stages, the planning phase of any trial must be conducted on a high ethical level to meet current standards set by the 3R’s principle of animal experimentation Replacement, Reduction, Refinement and by animal welfare authorities. In statistical practice, most studies are planned based on t-test type statistics and thus on strict distributional assumptions. Sample sizes are typically small and if planning assumptions are not met, the trials are underpowered and thus result in wrong conclusions and waste resources. On the other hand, nonparametric ranking methods are an excellent alternative data analysis method to such parametric approaches. However, neither sample size planning tools, group sequential designs nor sample size re-estimation methods have been developed and trialed yet in translational research environments.

This project aspires to contribute significantly towards improving the general work-flow in both preclinical, translational and clinical research in combination with innovative adaptive designs. This will be realized using modern nonparametric effect size measures with multiple contrast test methodologies. The corresponding statistical methods typically have a higher power than standard parametric methods when data is not normally distributed.

This project is a joint venture of the Department of Medical Statistics at the University Medical Center Göttingen the Institute of Biometry and Clinical Epidemiology at the Charité Universitätsmedizin Berlin. The project is funded by the German Research Foundation (DFG).

Investigators and Collaborators

Professor Tim Friede (principal investigator)
Department of Medical Statistics
University Medical Center Göttingen

Professor Frank Konietschke (principal investigator)
Institute Biometry and Clinical Epidemiology
Charité Universitätsmedizin Berlin and investigator of the project

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